Movement Lawyering and the<i>Caring Society</i>Litigation
Bibliographic record
Abstract
Abstract In 2016, the Canadian Human Rights Tribunal issued a landmark ruling in First Nations Child and Family Caring Society of Canada v. Canada finding that the government of Canada was racially and ethnically discriminating against First Nations children and their families in its funding and delivery of child welfare services to them. This ruling did not result from an isolated legal case; it was the result of litigation that was part of a broader social campaign with active supporters from all over the world. The litigation was driven by, and supported, a dynamic movement for sovereignty for First Nations Peoples around child welfare. This article examines the Caring Society case through the lens of movement lawyering—using the law to bring about transformative social change. Section 2 examines movement lawyering as an approach to lawyering. Movement lawyering involves a range of practices, advocacy and mobilizing that seek to dismantle architectures of subordination. Section 3 provides an overview of the Caring Society litigation and the social campaign within which the case was litigated. The I am a Witness campaign, a dynamic education and grassroots social campaign that engaged Indigenous and non-Indigenous children and sought to make the litigation accessible to the public, is examined in detail. Section 4 analyses Caring Society as a study of movement lawyering. It examines how three elements of movement lawyering; integrated advocacy; accountability to social movements; and willingness to address the root causes of structural oppression were at play in the litigation and related campaigns. In conclusion, the authors contend that Caring Society and the I am a Witness campaign constitute a successful example of movement lawyering as they properly recognize litigation, and the role of lawyers, as one piece of the mosaic of efforts needed to advance transformative social change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.034 | 0.068 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".